L’Espace géographique 2/97

This paper aims at comparing two kinds of discourses about the city, that of the microeconomics of cities, which is admitted in the realm of science, and that of utopian cities, which is not. We analyse the processes of thinking which lead respectively to theory and utopia, then we compare the ideas of man and society upon which they are grounded. Finaly, we try to enhance the similarities and disimilarities between the two series of urban space representations to which these approaches lead. This comparison may contribute to a better understanding of the real nature of the theoretical discourse and lead both to a relativization and a valorization of urban theory.

Denise PUMAIN. Towards an urban evolutionary theory (1 fig.)

Urban theories and especially urban economic theories adopt a static conception of cities (for instance central place theory or agglomeration economies theory). As a result their explanation of the urban phenomena neglect their genesis and urban change. Therefore, possibilities of prediction are reduced. To deal with cities which are complex objects, urban theory has to integrate dynamics and history. We propose here the premisses of an urban evolutionary theory, including self-organization processes. A few elements of this theory can be borrowed from dynamic models inspired by physical or biological theories of self-organization, but they have to be complemented by some specific social and spatial properties of urban systems.

Jacques-François THISSE. On the indeterminacy of regions and some resulting problems

It is shown that a region must be defined with respect to a particular relationship defined over a set of places. Some implications of this indeterminacy for the organisation of power and exchange are then discussed. On the whole the global conclusion is negative: a space of reference to be used for different purposes cannot be defined without creating distortions which turn out to be harmful for political and economic decision making. Nevertheless, partial solutions, inspired by modern economic theory, can be put forward.

Even if it is based, since its foundation in the fifties, on rational principles, regional science necessarily has to use representations, intellectual constructs depending on our social and cultural milieu of life. The objectivity-subjectivity question is linked to our scientific reasoning and cognitive approaches. This paper deals with the way regional scientists look at their object of research, to understand in a better way how we build a pertinent scientific knowledge in regional science.

A significant part of theory in economic geography is founded on the paradigm of economic choice behaviour. Some of its predictions, therefore, must be sensitive to the strong simplifications of this paradigm. This is why it seems useful to identify, discuss and evaluate those simplifications as they exist to-day. Toward this end, we compare models of choice behaviour in economics, including the most recent ones, with a standard paradigm of consumer behaviour in psychology and marketing. This comparison can give us a rather good measure of distance between experienced behaviour and economic behaviour, which is used as a basis in some parts of theoretical economic geography.

This paper shows that asymptotic models valid for spatial data often differ from commmon asymptotic models. Accordingly, asymptotic characteristics usually attributed to estimators, are no longer necessarily valid. Furthermore, taking into account changes of scale inherent to spatial processes leads to restrictions in model formulation and the econometrican should take this into account.

Spatial operations research problems seek «best» locations, often points of minimum aggregate weighted distance, requiring geo-referenced (locationally tagged) data as input. Frequently, maps of data are incomplete, and hence have holes in their geographic distributions. Statistical procedures, some of which explicitly exploit latent spatial autocorrelation, are available to complete these data sets with scientific guesses of values. Impacts such proxies have on location-allocation solutions are explored here, using 1986 Toronto and Ottawa-Hull, and 1980 and 1990 Syracuse population density census data. Geographical issues indexed by the sampling distribution of the spatial mean and standard distance are studied. Statistical issues of biasedness, efficiency, and frequency distribution are addressed. The Weber algorithm, a derivative of the standard Kuhn-Kuenne algorithm, is used to compute all of the single facility location-allocation solutions. Population density is used here as the weight attribute in determining location-allocation solutions because it can be quite accurately described with a relatively simple spatial statistical model.

The ultimate goal of urban land cover mapping using high-spatial-resolution images acquired by earth-orbiting sensors is to monitor both the extent of urban areas and their composition in terms of land use and, thus, to obtain accurate and consistent information on urban areas. Conventional classification techniques, however, have not always provided sufficiently accurate thematic maps. A fundamental problem is that conventional pattern classification techniques used are hard (crisp) techniques in which each image pixel is associated with only one class throughout the classification. Although this may be reasonable with some relatively fine spatial resolution remotely sensed data sets, coarse spatial resolution satellite sensor imagery such as that acquired by the Thematic Mapper are usually dominated by pixels of mixed land cover composition in urban areas. Failure to accommodate for mixed pixels will result in a poor representation of land cover distribution and incorrect estimates of class extent derived from it. This contribution shows how fuzzy set theory may be incorporated into the classification process, namely at the class membership level and at the output level with a measure of fuzziness to make aware of the vagueness of land cover classification obtained.